B-SPLINE STATISTICAL TECHNOLOGIES AND HAZARD REGRESSION

事件史分析方法在医学研究中被广泛使用 在临床试验，在药理学研究中，在研究 电离辐射在乳房和结直肠癌筛查中的作用 癌症，以及性传播疾病的研究。最近在那里 一直对生物统计学文献有相当大的兴趣 样条法在估计对数风险函数中的应用。我们建议 将这一领域的最新和正在进行的进展纳入Hare，这是一种产品 利用自适应多项式样条技术进行事件分析 历史数据。 当观察到的故障时间是由未知的 机制，兴趣通常在于估计风险、生存或 密度函数。在Hare中，这些函数是通过以下方法估计的 一元多项式样条及其选择的张量积 带协变量的多变量生存模型。使用类似火星的方法 以自适应地选择样条基函数。野兔也会计算 标准测试统计，提供易于使用的图形用户界面 具有广泛的指导能力，并全面图形化 显示计算的估计值和诊断。 建议的商业应用： 事件历史分析，特别是生存分析，是最重要的 大量使用的统计方法。Hare模块增加了一个令人兴奋的新功能 事件历史分析的维度。MathSoft打算将目标对准 生物医学和可靠性工程市场与野兔。这其中的每一个 市场代表了数以万计的潜在用户。这很难 设想统计软件领域的商业情况 更有可能成功。

Event history analysis methods are widely used in medical research: for example in clinical trials, in pharmacological studies, in studying the effects of ionizing radiation., in screening for breast and colorectal cancer, and in the study of sexually transmitted diseases. Recently there has been considerable interest in the biostatistics literature regarding the use of splines in estimating the log-hazard function. We propose to incorporate recent and ongoing advances in this area into HARE, a product utilizing adaptive polynomial spline technology for the analysis of event history data. When the observed failure times are generated by an unknown mechanism, interest often lies in estimating a hazard, survival, or density function. In HARE these functions are estimated by means of polynomial splines and their selected tensor products in univariate and multivariate survival models with covariates. MARS-like methods are used to adaptively select the spline basis functions. HARE will also compute standard test statistics, provide an easy-to-use graphical user interface with extensive guidance capabilities, and comprehensively graphically display the computed estimates and diagnostics. PROPOSED COMMERCIAL APPLICATIONS: Event history analysis, especially survival analysis, is one of the most heavily used statistical methods. The HARE module adds an exciting new dimension to event history analysis. MathSoft intends to target the biomedical and reliability engineering markets with HARE. Each of these markets represents tens of thousands of potential users. It is difficult to envision a commercial situation in the statistical software arena that is more likely to succeed.